• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.286-294
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• 2017

The events at the Fukushima Daiichi Nuclear Power Station in March 2011 point out, among other matters, that concurrent accidents at multiple units of a site can occur in reality. Although site risk has been deterministically considered to some extent in nuclear power plant siting and design, potential occurrence of multi-unit accident sequences at a site was not investigated in sufficient detail thus far in the nuclear power community. Therefore, there is considerable worldwide interest and research effort directed toward multi-unit site risk assessment, especially in the countries with high-density nuclear-power-plant sites such as Korea. As the technique of probabilistic safety assessment (PSA) has been successfully applied to evaluate the risk associated with operation of nuclear power plants in the past several decades, the PSA having primarily focused on single-unit risks is now being extended to the multi-unit PSA. In this paper we first characterize the site risk with explicit consideration of the risk associated with spent fuel pools as well as the reactor risks. The status of multi-unit risk assessment is discussed next, followed by a description of the emerging issues relevant to the multi-unit risk evaluation from a practical standpoint.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.04a
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• pp.27-34
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• 1997

In this paper, systematic and comprehensive approaches are suggested for the application of quantitative PRA techniques especially for those risk events that cannot be easily evaluated quantitatively In addition, dominant risk events are identified based on their occurrence frequency assessed by both actual survey of construction site conditions and the statistical data related with the probable accidents. Practical FTA(Fault Tree Analysis) and ETA(Event Tree Analysis) models are used for the assessment of the identified risks. When the risk events are lack of statistical data, appropriate Bayesian models incorporating engineering judgement and test results are also introduced in this paper. Moreover, a fuzzy probability technique is used for the quantitative risk assessment of those risk components which are difficult to evaluate quantitatively.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.380-386
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• 2017

Fennovoima's nuclear power plant, Hanhikivi 1, $Pyh{\ddot{a}}joki$, Finland, is currently in design phase, and its construction is scheduled to begin in 2018 and electricity production in 2024. The objective of this paper is to produce a preliminary list of safety-significant external event combinations including preliminary probability estimates, to be used in the probabilistic risk assessment of Hanhikivi 1 plant. Starting from the list of relevant single events, the relevant event combinations are identified based on seasonal variation, preconditions related to different events, and dependencies (fundamental and cascade type) between events. Using this method yields 30 relevant event combinations of two events for the Hanhikivi site. The preliminary probability of each combination is evaluated, and event combinations with extremely low probability are excluded from further analysis. Event combinations of three or more events are identified by adding possible events to the remaining combinations of two events. Finally, 10 relevant combinations of two events and three relevant combinations of three events remain. The results shall be considered preliminary and will be updated after evaluating more detailed effects of different events on plant safety.

• Nuclear Engineering and Technology
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• v.41 no.6
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• pp.849-858
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• 2009

Risk caused by safety-critical instrumentation and control (I&C) systems considerably affects overall plant risk. As digitalization of safety-critical systems in nuclear power plants progresses, a risk model of a digitalized safety system is required and must be included in a plant safety model in order to assess this risk effect on the plant. Unique features of a digital system cause some challenges in risk modeling. This article aims at providing an overview of the issues related to the development of a static fault-tree-based risk model. We categorize the complicated issues of digital system probabilistic risk assessment (PRA) into four groups based on their characteristics: hardware module issues, software issues, system issues, and safety function issues. Quantification of the effect of these issues dominates the quality of a developed risk model. Recent research activities for addressing various issues, such as the modeling framework of a software-based system, the software failure probability and the fault coverage of a self monitoring mechanism, are discussed. Although these issues are interrelated and affect each other, the categorized and systematic approach suggested here will provide a proper insight for analyzing risk from a digital system.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1140-1145
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• 2006

The railway human reliability analysis (R-HRA) plays a role of identifying and assessing human failure events in the framework of the probabilistic risk assessment (PRA) of the railway systems. This paper reviews three existing HRA methods including the K-HRA (THERP/ASEP-based) method, the HEART method, the RSSB-HRA method, and introduces a case study that was performed to select an appropriate method for a railway risk assessment. The case is the signal passed at danger (SPAD) events, which are caused from a variety of factors. From the case study, the strengths and limitations of each method were derived and compared with each other from the viewpoint of the applicability to the railway industry.

• Journal of the Korean Society for Railway
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• v.9 no.5 s.36
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• pp.532-538
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• 2006

The railway human reliability analysis(R-HRA) plays a role of identifying and assessing human failure events in the framework of the probabilistic risk assessment(PRA) of the railway systems. This study introduces a case study that was performed to select an appropriate R-HRA method. Three HRA methods were considered in the case study: (1) the K-MRA(THERP/ASEP-based) method, (2) the HEART method, (3) the RSSB-HRA method. Two case events were selected based on the review of the railway incidents/accidents, which include (1) a real-end collision event, which occurred on the railway between the Gomo and Kyungsan stations in 2003, (2) the signal passed at danger(SPAD) events, which are caused from a variety of factors. The three HRA methods were applied to both case events, and then the strengths and limitations of each method were derived and compared with each other from the viewpoint of the applicability of a HRA method to the railway industry.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2924-2932
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• 2022

Motivated by learning from experience and exploiting existing knowledge in civil nuclear operations, we have developed in-house generic Probabilistic Safety Assessment (PSA) models for pressurized and boiling water reactors. The models are computationally light, handy, transparent, user-friendly, and easily adaptable to account for major plant-specific differences. They cover the common internal initiating events, frontline and support systems reliability and dependencies, human-factors, common-cause failures, and account for new factors typically overlooked in many PSAs. For quantification, the models use generic US reliability data, precursor analysis reports, the ETHZ Curated Nuclear Events Database, and experts' opinions. Moreover, uncertainties in the most influential basic events are addressed. The generated results show good agreement with assessments available in the literature with detailed PSAs. We envision the models as an unbiased framework to measure nuclear operational risk with the same "ruler", and hence support inter-plant risk comparisons that are usually not possible due to differences in plant-specific PSA assumptions and scopes. The models can be used for initial risk screening, order-of-magnitude precursor analysis, and other research/pedagogic applications especially when no plant-specific PSAs are available. Finally, we are using the generic models for large-scale precursor analysis that will generate big picture trends, lessons, and insights.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.129-141
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• 1987

The possibility of human error in operation of nuclear power plant has been proved to be one of the most important factors for safety analysis. This study established the HRA methodology according to THERP steps for performing PRA(probabilistic risk assessment) of nuclear power plants and made two sample calculations : Availibility of auxiliary diesel generator, possibility of Davis-Bess #1 accident in 1985.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.376-385
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• 2021

Probabilistic risk assessment (PRA) has improved its elemental technologies used for assessing external events since the Fukushima Daiichi Nuclear Power Station Accident in 2011. HRA needs to be improved for analyzing tasks performed under extreme conditions (e.g., different actors responding to external events or performing operations using portable mitigation equipment). To make these improvements, it is essential to understand plant-specific and scenario-specific conditions that affect human performance. The Nuclear Risk Research Center (NRRC) of the Central Research Institute of Electric Power Industry (CRIEPI) has developed an HRA guide that compiles qualitative analysis methods for collecting plant-specific and scenario-specific conditions that affect human performance into "narratives," reflecting the latest research trends, and models for analysis of tasks under extreme conditions.

• Nuclear Engineering and Technology
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• v.17 no.4
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• pp.302-316
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• 1985

Small break LOCA caused by a stuck-open PORV is one of the important contributors to nuclear power plant risk. This paper deals with the design of a pressurizer surveillance system using microcomputer to prevent the malfunction of system and has assessed the effect of this improvement through Probabilistic Risk Assessment (PRA) method. Micro-computer diagnoses the malfunction of system by a process checking method and performs automatically backup action related to each malfunction. Owing to this improvement, we can correctly diagnose “Spurious Opening”, “Fail to Reclose” and “Small break LOCA” which are difficult for operator to diagnose quickly and correctly and reduce the probability of a human error by an automatic backup action.